Article
Licensed
Unlicensed
Requires Authentication
A Note on the Hiemstra-Jones Test for Granger Non-causality
-
Cees Diks
Published/Copyright:
June 6, 2005
We address a consistency problem in the commonly used nonparametric test for Granger causality developed by Hiemstra and Jones (1994). We show that the relationship tested is not implied by the null hypothesis of Granger non-causality. Monte Carlo simulations using processes satisfying the null hypothesis show that, for a given nominal size, the actual rejection rate may tend to one as the sample size increases. Our results imply that evidence for nonlinear Granger causality reported in the applied empirical literature should be re-interpreted.
Published Online: 2005-6-6
©2011 Walter de Gruyter GmbH & Co. KG, Berlin/Boston
You are currently not able to access this content.
You are currently not able to access this content.
Articles in the same Issue
- Article
- Economic Growth and Revealed Social Preference
- A Test of the Martingale Hypothesis
- Solving Ramsey Problems with Nonlinear Projection Methods
- A Note on the Hiemstra-Jones Test for Granger Non-causality
- Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model
- What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study
- Joint Tests for Non-linearity and Long Memory: The Case of Purchasing Power Parity
Articles in the same Issue
- Article
- Economic Growth and Revealed Social Preference
- A Test of the Martingale Hypothesis
- Solving Ramsey Problems with Nonlinear Projection Methods
- A Note on the Hiemstra-Jones Test for Granger Non-causality
- Bayesian Analysis of a Doubly Truncated ARMA-GARCH Model
- What Causes The Forecasting Failure of Markov-Switching Models? A Monte Carlo Study
- Joint Tests for Non-linearity and Long Memory: The Case of Purchasing Power Parity
